Irvine, California, United States
Experienced Software Development Engineer in Test with a robust background in designing and developing automation frameworks and performance testing. Proficient in a wide array of technologies including JavaScript, Java, Python, React, Node.js, and cloud services such as AWS. Demonstrated expertise in both manual and automated testing across various tech stacks, with a proven track record in improving system performance and ensuring data integrity. Strong collaborator with experience working in agile environments alongside project managers, software engineers, and data scientists.
• Designed and built a Playwright + TypeScript automation framework from scratch (page objects, fixtures, reusable helpers), reducing end-to-end testing time by ~3 days per sprint. • Integrated automation into GitHub Actions CI/CD to run on merges and deployments across environments; scaled automated coverage from ~5% to ~90% of priority critical flows in under a year, significantly reducing manual regression. • Stabilized nightly test runs by diagnosing flaky failures (timing issues, environment data, selector brittleness) and refactoring tests to be deterministic and self-validating. • Owned test strategy for the web app, mapped high-risk flows, defined PR gates vs nightly suites, and drove a release-ready regression checklist for each deployment.
• Developed and scaled UI + API automation using JavaScript, Cypress & WebdriverIO, Jest, Docker, and AWS; created hundreds of automated tests achieving ~95% functional coverage of critical user journeys and high-risk edge cases and reducing production defects by ~65%. • Built performance testing suites (JMeter, k6/Grafana, Datadog) to validate reliability under load; surfaced latency regressions and memory leaks impacting production systems. • Contributed to internal tooling and platform work (Spring Boot, React, GraphQL, REST Assured, AWS), improving testability and increasing Verification Agent throughput by ~30% per week.
• Built a Java/Selenium regression suite to validate data correctness and completeness for a web application post-ETL pipeline processing. • Validated ETL data consistency with SQL across Hive, Netezza, MySQL, and Postgres; investigated discrepancies and documented root causes. • Authored test cases, documented results, and reported defects; partnered with developers, BAs, and leadership to drive resolution.